Essays about: "graph neural networks"
Showing result 21 - 25 of 82 essays containing the words graph neural networks.
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21. Information Extraction from Invoices using Graph Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Information Extraction is a sub-field of Natural Language Processing that aims to extract structured data from unstructured sources. With the progress in digitization, extracting key information like account number, gross amount, etc. from business invoices becomes an interesting problem in both industry and academy. READ MORE
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22. Impact of the autoencoder-based FINTA tractogram filtering method on brain networks in subjects with Mild Cognitive Impairment
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Diffusion Magnetic Resonance Imaging (dMRI) is a method for measuring molecular diffusion in biological tissue microstructure. This information can be used to predict the location and orientation of white matter fibers in the brain, a process known as tractography. READ MORE
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23. Artificial Neural Networks and Inductive Biases for Multi-Instance Multi-Modal Tabular Data : A Case Study for Default Probability Estimation in Small-to-Medium Enterprise Lending
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The success of artificial neural networks in homogeneous data domains such as images, textual data, and audio and other signals has had considerable impact on Machine Learning and science in general. The domain of heterogeneous tabular data, while arguably much more common, remains much less explored with regards to artificial neural networks and deep learning. READ MORE
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24. Expressibility of multiscale physics in deep networks
University essay from Umeå universitet/Institutionen för fysikAbstract : Motivated by the successes in the field of deep learning, the scientific community has been increasingly interested in neural networks that are able to reason about physics. As neural networks are universal approximators, they could in theory learn representations that are more efficient than traditional methods whenever improvements are theoretically possible. READ MORE
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25. Modelling Cyber Security of Networks as a Reinforcement Learning Problem using Graphs : An Application of Reinforcement Learning to the Meta Attack Language
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : ICT systems are part of the vital infrastructure in today’s society. These systems are under constant threat and efforts are continually being put forth by cyber security experts to protect them. By applying modern AI methods, can these efforts both be improved and alleviated of the cost of expert work. READ MORE
